Our main use case for Cribl was primarily data reduction, as we were spending a lot of money on data ingest, and we brought Cribl on board to reduce the amount of money we were spending on that ingest.

Reduction in firewall logs was our primary use case for Cribl, as 80% of our data is Palo Alto firewall logs, and a lot of it we don't necessarily need in the SIEM tool, so we use Cribl to reduce that, keep only the stuff we want, drop the rest, and keep it out of the SIEM tool. The reduction in firewall logs keeps the unwanted data out so that when the security engineers are inside the SIEM tool, they only see the stuff they need to see.

The features of Cribl that I appreciate the most are the vendor agnosticism and the ability to send data almost anywhere you want, regardless of the data type, the format, or the destination; it's very flexible, and we've been able to integrate it with the tools that we have used in the past and are planning to use in the future.

The UI is very clean and super intuitive, making it very easy to bring data on via the sources, route the data to any number of destinations that you want, and create pipelines to transform and morph that data however you want.

Cribl is great in the sense that it can handle a large amount of volume and scales with the amount of data that you want to bring on board; if you need to bring on board more data, you just increase the amount of workers that you have.

We use Cribl to reduce data cost and complexity by both dropping fields that we don't want or parts of events that we don't want while keeping the things we do want, while also keeping all of the data, the event in its full form. We're a government agency, so we ned to keep everything. With Cribl, we can have our cake and eat it too, in a sense.

I'm an engineer, so I think about logging. Improvement could be made in the logging area, as sometimes we encounter issues in a pipeline or something, and it's not immediately obvious when you look at the logs that the pipeline is failing.

I've been using Cribl for around four years.

I would give Cribl a great rating on stability and reliability, especially if you use the built-in alerting engine that they have, as you can get alerts directly if there are any problems with the worker itself or worker processes, and the built-in monitoring page makes it super easy to monitor the health of all your worker processes.

Cribl scales great with our company as we're actually bringing on a lot more data with all the AI tools rolling out, which generate a lot of logs, and Cribl scales horizontally by just adding more workers and worker processes, allowing us to tackle that data smoothly, quickly, and efficiently.

We've had a great experience with Cribl customer service, as we have dedicated PS resources that have been super helpful when we were rolling out Cribl initially, migrating sources of data from syslog over to Cribl, routing, and parsing, with the support being A+ on both the PS side and the technical support side.

Cribl is really the only tool out there that does what it does, especially when looking at Splunk, as when Cribl first came out, Splunk wasn't able to intuitively do a lot of the things that Cribl did just out of the box with a GUI, making it super easy.

We were dabbling in data reduction, transformation using Splunk's Universal Forwarder and even the Heavy Forwarder in some instances, but it was just not as intuitive, with a lot of command line interaction and no GUI on the front end, making it harder to do, while Cribl makes it super easy.

When we deployed Cribl, we were on-prem. All of our workers are on-prem. Our leaders are on-prem. Nothing's in the cloud. The major challenges that we faced really were related to the load balancer that needs to sit in front of the workers. I would like to maybe see that rolled up into Cribl in the future. That posed a lot of challenges for us just coordinating with our infrastructure team, getting the F5 engineers involved, using F5 load balancer. That was a challenge for us. We ultimately tackled it, however.

From my point of view, the biggest return on investment is just the downstream licensing costs we save on the SIEM side; we've reduced our data by a certain amount, and it has almost paid for Cribl itself and also allowed us to chop some licensing off of the SIEM side. We've reduced our amount of ingest by about 40% overall.

I'm not really involved in the pricing and payment aspect of Cribl. I'm just the guy who implements it all once it's bought and paid for.

We're not using Cribl Search at the moment; we're only using Stream and Edge.

If you're a company out there considering Cribl, I would highly recommend at least giving it due diligence; get linked up with the sales rep, as they're going to explain everything to you, and the sales engineers are great and very knowledgeable, making it worth your time and money, so you're going to be glad you did.

I rate Cribl nine out of ten.

Our main use case for Cribl is primarily taking data from all of our different data sources, doing some processing, field extractions, normalizing the data, and then sending it along to our SIM for security incident response and investigation.

My favorite feature of Cribl is just how easy it makes working with the data; it's always been a pain point for us with other solutions, just taking our raw data from the source, transforming and manipulating it into what we need on the SIM side. That's always been a pretty heavy lift, however, Cribl has made that much easier.

The tools built into the platform allow us to work with the data, see the results in real-time, see what the output's going to look before we commit it, and has really made our job in that respect a lot easier.

The Cribl UI is very simple and easy to use, particularly when working with data from various sources; it makes it very easy to create pipelines, add complex logic to those pipelines, and then gives you a preview of what your data looks like before applying that pipeline and what you get after.

As we're bringing data in and Cribl's processing it, it makes it very easy to identify subsets of data or certain events that source data that maybe are less useful or just noisy, not really applicable to to what we need what our security team needs, and we're able to just drop those events before they get sent out and and ingested by our SIEM. So that helps keep our data pipeline streamlined, keeps our output clean. It filters out noise, and then it makes our analysis more efficient. That reduces the data volume going into our SIMs, and that reduces and limits the ingest costs associated with that end. With less data, there's less to process when you're running complex searches. So we have charges against those compute resources reduced.

There are opportunities for AI to be incorporated more tightly into Cribl to help build out those pipelines and apply some more complex logic to those transformations could be useful.

Optimizing CPU utilization on the edge side is something that could be improved; we see, particularly on older hardware and older OSes, Cribl Edge service can eat up quite a bit of CPU resources compared to some other products we've used in the past, indicating there's room for improvement.

We've been using Cribl for about one year.

We have run into a few performance issues and system crashes, mainly due to administrator error; building inefficient pipelines ended up utilizing or over-consuming CPU resources on the worker server, causing some outages. We've worked with Cribl support to resolve those issues, and it's been pretty stable recently.

As we've only been using Cribl for about a year now, I view many of those issues as part of learning the product and becoming better stewards of the system.

We've only been using Cribl for about a year, so we haven't really seen much expansion and are still in a holding pattern. However, leveraging cloud resources does provide the ability to scale; we can provision additional servers on-prem to handle more data load as we scale up and bring on more resources, so I'm confident we'll be able to meet our future demands.

When we've had issues with Cribl, the support we've received has been fantastic; they've been very responsive.

Our account team has stayed on top of the issues we've submitted, and all of the technicians we've worked with have been very knowledgeable, so we've been very happy with Cribl support overall.

On a scale of one to ten, I would give customer service a nine; I'm hesitant to say ten out of principle. There's always room for improvement.

The technicians we've been paired with on the cases we've submitted have all been knowledgeable and responsive. Our account team has been great, and when we've raised questions or concerns, they're quick to provide assistance.

Our primary driver behind implementing Cribl was the need to normalize our data with our existing SIM solution at the time; we had numerous problems making it easily searchable and analyzable. With our previous solution, we easily onboard new data sources, however, as we did that, we weren't necessarily taking the time to properly extract the fields out of that data that we needed.

Consequently, we ended up with a lot of data that was either not helpful or just not usable at all, which just consumed costs and space. Cribl addresses this by allowing us to easily create those pipelines and manipulate the data so that we could reduce the amount of information that we're ingesting that was not useful.

Overall, the deployment of Cribl was very easy. We did not really run into too many challenges at all.

We deployed a hybrid architecture, so we primarily leverage the Cribl cloud. We also have some on-premises workers who we have connected to the cloud. It's a cloud-connected, yet independent leader and has worker nodes for processing edge data from offline edge nodes. So those systems are in secure VLANs and don't have outbound internet access. We're able to stand up an on-premises infrastructure that is still cloud-connected, that's part of our overall environment, and can capture that data and send it along to our system. So overall, we really did not have any challenges standing up the infrastructure. It's been very easy to stand up and maintain.

The return on investment for Cribl is that we've seen it really pay for itself.

When we recently went through a SIM migration from Splunk to Microsoft Sentinel, we incorporated Cribl to help us reduce our ingest costs. What we've seen is really an overall reduction of just shy of 40% in our ingest into our SIM platform versus prior to having Cribl, and those ingest costs have basically canceled out the pricing of Cribl licensing for us based on the volume of data that we have.

I don't recall considering other similar solutions to Cribl. Cribl was the frontrunner on that one. We did a proof of concept early on and immediately saw how easy it was to work with the data and recognized the value it could bring, leading us to move forward with it.

I would advise other companies considering Cribl to just do it; it's worth it, as there's really little to no downside. It just makes your life easier.

On a scale of one to ten, I would rate Cribl a nine, as it brings tremendous value.

As a small security team, it really empowers us to get more useful data out of our sources, making our SOC and incident response teams more efficient and improving the overall security posture of our organization as we now have accurate, usable, easily analyzed data.

Security data is my main use case for Cribl. I ingest data using Cribl Edge and then process the data using Cribl Stream to reduce the amount of volume of the data collected for use in other platforms.

The Cribl Edge features that are easier to use or to manage help me to reduce the amount of people I need to help manage the product.

As part of Stream, reducing the amount of volume provides a financial benefit to allow us to pay less for the other products that we are using the data in down the data path or stream.

The ease of management and configuration of Cribl Edge features is highly beneficial. I have many thousands of Cribl Edge nodes deployed, and it's very easy to make configuration changes across the board or update the agent.

It can contain data cost and complexity. In terms of data complexity and cost, Cribl does a good job at providing solutions that will compress the data while retaining its usable form, or split the data in such that you can retain its original form and send a reduced form to your end destination. In terms of reducing the amount of logs with Cribl for firewall specifically, I am able to reduce the size and reformat the logs so that they are better able to be used downstream.

Cribl has influenced the data processing workflow by allowing us to be platform-agnostic, and being able to separate the data into different destinations is quite easy.

The Cribl UI in general is very intuitive in how to manage log processing and configurations. Customer service and support deserves an 8.5 rating. They are really good at what they do, and you can tell that they are passionate about their product and helping customers have success.

Cribl could be improved by some UI tweaks and some usability tweaks, mostly centered around error troubleshooting for large volumes of Edge nodes.

I have talked to the developers of the Cribl Edge software and they're very open and welcoming to the feedback and are looking to implement changes to help make the product better.

I have been using Cribl for a few months since July of 2025.

Cribl is overall a very reliable product and solution. The few times that I've had any reliability issues, they were quick to help me identify and proactive in helping me identify potential issues in the platform.

We have over 10,000 employees.

Cribl does a good job of handling large volumes of data very quickly. The Cribl Cloud that we have deployed allows for easy scaling to meet the needs of onboarding tens of thousands of Cribl Edge devices in a single day in some cases. Cribl makes scaling for Edge or Cribl Cloud data nodes very easy to add or replace Cribl worker nodes and allows you to, with one click, reconfigure Cribl Cloud workers to be able to ingest higher volumes of data.

Cribl technical support and customer service has been great so far. I really appreciate having a direct line to my Cribl SE or many different Cribl private resources via their Slack channel.

It is a really easy way to quickly get an answer on something rather than having to put in a support ticket, however, support tickets are also fairly straightforward and easy to use.

I did not use other solutions before Cribl that do the same thing as Cribl does.

My experience for deploying Cribl was pretty easy. We have Cribl Cloud, and they make that a very simple solution to stand up. And for the on-prem resources that we have for Cribl workers, those were also easy to stand up and get connected to the cloud. So, overall, it's very easy to deploy the platform and to get it to configure.

The biggest return on investment is probably the log reduction capabilities while retaining the essential information from the logs. In some cases, greater than 80% reduction is achievable. Across thousands of endpoints, it really adds up quickly.

The pricing for Cribl was fairly straightforward. They have a universal license that allows us to consume the portions of Cribl that we want to use or flex into other portions of Cribl. We primarily use Cribl Edge and Cribl Stream at this point, but we could also use the same license for Cribl Lake or Cribl Search.

I did not consider other solutions in my company before choosing Cribl.

I've worked in information security for over ten years.

With any SaaS solution, it's sometimes a difficult decision to decide to do on-premises versus a SaaS solution for on-cloud. I would recommend Cribl on Cloud for its ease of use and manageability. The managed updates are very nice and they have a proactive services team that helps monitor the infrastructure.

Overall, I would rate Cribl nine out of ten. While there are some shortcomings, the direct feedback loop they give to customers makes it a really good product overall.

My current use cases involve using it as a pipeline to process data, to route data from cloud logs to different repositories. Some data goes to Splunk and others go to different data lakes. I didn't work with the firewall logs directly. We use Cribl to process web activity and route data that we wanted to into Splunk ES to create detections.

What I appreciate the most about Cribl is the free training, the free access to all the training, and how easy it is to learn it. Cribl is great in handling high volumes of diverse data types, such as logs and metrics. It does the job.

The product is very good. They could add more AI-assisted pipeline development in the future release.

I have been using Cribl for six months.

I haven't seen any lagging or crashing with Cribl.

Cribl's scalability is very good.

I have never contacted the technical support or customer support of Cribl.

The initial deployment when I first started with Cribl was fairly easy, very easy.

We were a team for this job.

I have used alternatives to Cribl. I forgot the name, but it's a CrowdStrike product they just acquired that is the closest one I've used to Cribl in terms of the quality and the features. Currently, I prefer Cribl more than CrowdStrike. I still haven't played much with the other one, but I didn't find any issues with Cribl.

Regarding Cribl's ability to contain data cost and complexity, if they can reduce their cost, that will make them more competitive. However, I don't know what else they can do in regards to how the application works. It's very good.

For the project that I was involved in, it took me probably three weeks to set it up. We had to maintain our pipelines, not because of anything related to Cribl itself, but because the data source changed, so we had to adjust our pipelines. That was the kind of maintenance that we did.

I would rate Cribl a nine out of ten.

Our use case for Cribl is actually a data pipeline where we collect logs from the source and we stream it through Cribl and then to a destination. The destination is mainly the SIEM tools such as CrowdStrike or SecOps. We collect the logs from various sources, and even the Windows logs are streamed through Cribl worker nodes and data lakes. For example, if it is AWS, from the S3 bucket we stream to Cribl and then send it to Google SecOps, which is the primary SIEM we are using.

The best feature in Cribl, when getting logs from some custom application, is the ability to break up logs that pile up together and come as one event.

Cribl has a feature called JSON Unroll or Unroll function that allows you to differentiate the events; each event will come ingested as a single log instead of piling it up with multiple events. This is critical as this generally happens in CrowdStrike. This feature helps us significantly.

When the ingestion is high from unwanted logs, logs not related to security purposes can be dropped by writing the parser function. By dropping events that are not required for security purpose monitoring, we can reduce the ingestion, which drastically reduces the cost as well. Cribl gives another option where I can store some logs, and when needed, I can pick them up from there.

The interface is very handy and not very complicated, yet there are many functions you can perform. You can play around with numerous functions, parse there, and add UDMs to SecOps, which makes it really easy.

To simplify the pipeline, when we go to the pipelines, there are vast options. We can make it specific requirements based on the customers. I would prefer a customized or simplified version. Cribl is a very good platform to work with, with lots of features that other platforms don't provide.

Cribl is a stable product, however, there are areas for improvement. Their documentation should be updated.

I have been using Cribl for a year and a half.

Cribl is a stable product, but there are areas for improvement. Since Cribl is on-premises, server maintenance is required, and we have an IT team specifically to look into that. We are not worried about that.

There is a similar platform by Google called BindPlane, which is not capable of handling high volumes of data as the data gets stuck in the pipeline, causing ingestion delays.

However, Cribl does not present that problem. Since I have worked with both data pipeline tools, I can compare and say that Cribl is more mature than others.

I have not reached out to Cribl support. That said, my colleagues have.

I'm using another product called BindPlane, which does almost the same things; however, Cribl is a very mature product with many functions. You can use the Eval function, Unroll function, break events, add any particular field you want, or parse in Cribl before sending to a destination.

The initial setup involves dropping some events that are not required for security purpose monitoring. This is based on suggestions from our SOC team or customers.

The deployment itself is a bit compicated and the documentation is not very clear.

We are a partner with Cribl. We have CrowdStrike, and CrowdStrike has partnered with Cribl; they even changed the name to CrowdStream.

It has saved my cost and our customers' cost drastically since I cannot drop the logs directly in SIEM. In Cribl, I can drop the logs, and when I'm not ingesting them, their licensing cost is drastically reduced.

Cribl Search is quite handy; you can use regex where there's a function that contains, and you can search for a specific keyword, which shows everything that matches that keyword. After playing around a couple of times, it becomes easy. At first, it is complicated; you need to go to worker groups, select the data lake, select the worker node. Once you get used to it, it's quite handy. I would definitely recommend Cribl to other users.

Based on my experience, I would rate Cribl eight out of ten.

Our use case for Cribl is that we want to make sure that we parse everything correctly, and it is easier for us to transfer our data in our system in a more compact way; it runs smoothly.

We're in the beginning stage of using Cribl, but the reduction in firewall logs will help significantly with processing speed. We just worked on handling high volumes of diverse data including logs, metrics, and files last week, and it ran very smoothly with quick processing.

The best feature about Cribl is how easy it is to move; the UI is very simple, everything is very neat, and everything is organized. We have been dealing with Cribl extensively recently.

Cribl is awesome. The university offers a lot of great resources, but there could be more detailed information about Cribl itself. It would be helpful to have a step-by-step guide that covers everything from the basics. Since Cribl is such a large platform with numerous features, having a clear, structured approach would make it easier for me and others to understand and utilize its capabilities.

I believe it would be beneficial to have a step-by-step guide for users on our endpoint. This would make it easier for them to understand how to use it. When I explored the endpoint, I found myself wishing for clearer instructions presented in a sequential manner. This is just a small critique based on my experience using it so far.

We started using Cribl around three months ago.

I would rate stability as a nine; nothing is perfect, but it's great.

I would definitely give scalability a nine as in terms of what we're seeing and thinking about, it's solid.

We have around eight or nine users. Everyone is touching base with it. For now, it will stay at eight unless we expand. We are going through an expansion, so it’s possible we might increase the number of users; but for now, we’re steady at our current count. We are a medium-sized business.

Their customer support is fantastic.

We were using a manual solution previously; this transition to Cribl is our first time implementing an automated solution.

We are typically on-premises. I believe Cribl is currently focused more on the OT side because the primary customer base is more enterprise-oriented. OT relies heavily on this. However, if I'm not mistaken, we operate in an on-premises or hybrid environment; we are definitely not using the cloud.

We are still in the process of deployment, and so far, the deployment has been going fairly well and has been relatively quick for us.

We are in the transitioning stage; we're implementing everything from square one with our team, participating in daily calls to make that happen. We are experiencing some issues with data transfer and parsing errors, which is extending our SIEM transfer time.

Based on what our managers say, we have saved a significant amount of time and resources moving from a manual approach to something that's more automated.

As I visited different booths at the conference, I realized that I still prefer Cribl. Even though I haven't worked with any other platforms, I was impressed by how everything is laid out and how simple it feels to work with your system. I genuinely appreciate the user interface. I find it straightforward and well-organized, making it easy to navigate.

I also noticed that they have implemented something like a password manager, which sounded familiar. Overall, everything I saw reaffirmed my preference for Cribl. So, despite checking out various booths, I'm still committed to Cribl at the end of the day.

I would definitely recommend it. The user interface is great, and the customer support has been fantastic as well. Our experience with Cribl has been very smooth; everything runs seamlessly. There are no delays or sluggishness, which I really appreciate. I have to give it props for that; everything operates very smoothly.

I would rate Cribl a nine out of ten.

Our main use case for Cribl was SIEM migration, where we merged multiple SIEM solutions to a single SIEM solution. SIEM migration was the most major use case we were looking for. The second use case was a manageable logging solution which could have a nice interface and would be easy to manage. Data cutoff or Log Filtering was the third biggest use case we were looking for, where we were seeking data reduction to define what we need and don't need. Additionally, we performed data masking for PII i.e. payments and medical data. These were the main use cases that were all provided by Cribl.

My previous company did a significant amount of business using Cribl, particularly in servicing customers who had a perfect fit for the solution. From a consultant's perspective, I can say that we resold licenses for Cribl, delivered services related to Cribl, and also provided maintenance services. This brought a decent amount of business to our company.

Regarding the reduction in firewall logs due to Cribl, it did influence our overall data processing and workflow. For example, the AWS VPC flow logs were greatly reduced in size, which had a substantial impact on the licensing costs for destination platforms. It did help us and the customer quite a bit. Cribl's role in its reduction of firewall logs, either cloud or on-prem, was vital.

The data cost is an important aspect. Cribl is specifically designed to reduce the data costs associated with the destination platform. This is one of its core offerings.

Regarding platform usability, the Cribl interface is quite intuitive and easy to use. The navigation and seperate sections are easily accessible, making it very user-friendly. The color scheme and palette are excellent, and there’s nothing messy or unmanaged about the user interface. Overall, I personally find the user interface to be very comforting.

The features of Cribl I have found most valuable include its SIEM migration capability. It facilitates migration quite nicely. The data reduction and preprocessing capabilities make Cribl really unique. Data masking is an important one. And as Cribl Stream can be deployed on-prem, on cloud or as a hybrid model, its support for every sort of enterprise estate is highly appreciated.

The UI interface is very good. It's user-friendly, intuitive, not complicated, and sufficient. It's not more than what it needs to be, and it's simple without being overly complicated.

They've already done many good things with the product, but perhaps they could implement a temporary SIEM solution where we could store logs and display them as a SIEM, though I think that's not the space that Cribl is actually looking into. Based on my experience, this product is brilliant and there isn't much or anything important lacking in the product.

We encountered some occasional issues with the syslog data stream, particularly when handling large data volume, and getting it to parse and field extracted correctly, but no major alarms that would halt the days operation. There were few source vendor specific challenges, but overall, I didn't notice anything major beyond that. Most of the process went smoothly. However, we did need to carry some troubleshooting to resolve the issues we faced while connecting with other platforms and few data stream miss-behaving, which wasn't a straightforward task for us. In terms of large datasets—whether they originated from network inputs, virtual machines, or cloud instances—ingesting the data into the destination was relatively easy. In summary, aside from the usual difficulties or issues that someone could face with any project, everything else went well.

I have been working with Cribl for more than four years now.

Cribl is quite stable and doesn't crash; there's no unusual behavior. If it's stable, then it's reliable. I could see the data that goes in and how it is being processed at each stage. There are no concerns when Cribl is working in production environment.

Cribl is quite scalable, as we could add worker nodes as our data grows, so it's sufficiently scalable and able to facilitate as much data as there can be.

Their technical support has been really great, and solution architects we worked with were really knowledgeable. They had extensive expertise with the product and were able to facilitate with everything we needed. The experience with Cribl technical staff has been one of the best.

For similar use cases, different companies were using different tactical solutions i.e. custom scripting. None of the solutions were strategic and well thought through. Some were using scripting, some were not utilizing anything. Some were ingesting into the SIEM and then doing all the tasks which should be done pre-ingestion. There was a lot of disorganization, and Cribl had really found the gap where they could offer their services.

I performed the entire setup of the Cribl infrastructure.

With the Cribl Stream setup, I first had to initiate the tenant. Once the tenant was provisioned, I configured IAM setup i.e SSO, RBAC etc. I onboarded the data sources and deployed the worker nodes to the appropriate locations. These locations could be various subnets, cloud virtual machines, on-premises virtual machines, or any ready-to-use Cribl cloud workers we needed. The process depended on the company's IT infrastructure. After the worker nodes were set up, it was simply a matter of onboarding the data stream into the platform and then directing it to the destination platforms.

As for Cribl's deployment, it operates in a hybrid environment, utilizing both cloud and on-premises solutions, tailored to meet the needs of different customers.

I delivered Cribl services as a Certified Cribl Consultant to various customers. Cribl technical support was arranged whenever there was a need for it.

We have managed to save significant money and resources for multiple customers, reducing operational complexity and the cost of destination platforms but unfortunately I cannot quote specific numbers due to NDA.

Cribl is very inexpensive, with enterprise pricing around 30 cents per GB, which is really decent. Organizations looking to ingest terabytes or petabytes of data each day find it quite an inexpensive solution. The pricing model for Cribl Stream is one of the best values that customers would be getting, and I don't think any other solution offers this much value at this price point.

Confluent was considered, but Cribl emerged as the best solution.

I would rate Cribl an eight out of ten.

For Cribl, we use only Stream, which we are using as a data pipeline in between our environment and the SIEM console. We have two SIEMs: one is a cloud SIEM and one is an on-prem SIEM. On-prem, we are using another user and entity behavior analysis tool, so we have a redirection or a copy of a log for user login and logout information. Then we have a SIEM console, and we have redirections to the SIEM through Cribl. From the environment, we have a load balancer, and from the load balancer, we have this data pipeline configured to different SIEMs, and then we have that data transferred to two different SIEMs.

Cribl's ability to handle high volumes of diverse data types is exactly the purpose that we took it for, and as far as I have seen for the last nine months, it is handling well without issues. Connectivity-wise, there is some problem, but I'm not sure whether it's from the Cribl end or the SIEM end; we are working on both ends right now, so I don't see any problems concerning that. Cribl has helped in reducing informational logs between the main entity of our SIEM and the external entity, so that actually helped.

Regarding Cribl's solution, we have limited access to Stream. I'm not sure about the other three products. We only use the Stream of Cribl. If I suggest something, it may be available on the other products. I haven't worked on those. The suggestion would be more into log information, as I'm not able to view more logs because this is a limitation that we are only using for data pipelining. If we have more visibility or if the storage structure is already there, I'm not sure; if it is there, it would be fine.

Regarding stability, lagging only happens if I exceed my data analysis stuff, but it is a limitation with Cribl as per their design. We do not use it for that purpose, but if it is improved, it would be great. For scalability, I'm not sure in my project as we are using it only for a limited purpose. Maybe, if there was an environment that required more data transfers and logs to be filtered out, it would be good, and I would suggest it.

I have been using Cribl since we deployed it during November, which is close to nine months.

We are actually checking on a regular basis; however, the problem is with the connectivity of the data pipeline and the SIEM. It requires attention if there is an alert; for example, if the pipeline is down and we receive an alert that it's not sending information to the log collection platform for more than one or two hours, if we receive an alert, it would be great.

For scalability, I'm not sure in my project as we are using it only for a limited purpose. Maybe, if there was an environment that required more data transfers and logs to be filtered out, it would be good, and I would suggest it.

My engineering team contacts Cribl's technical support; I join the call in case any issues come up and I provide my suggestions.

Cribl is the first tool that I'm using for this particular data pipelining. We do have Dynatrace, but we use it for a different purpose, for monitoring. Cribl is for streaming purposes only, so the purpose is different. I'm not sure if there is a competitor for this particular tool or not, as I haven't worked with any competitor so far.

The initial installation was kind of easy to understand for me, while my teammates struggled a little bit, so I would say it was okay.

My engineering team contacts Cribl's technical support; I join the call in case any issues come up and I provide my suggestions.

Cribl is the first tool that I'm using for this particular data pipelining.

For everything, my suggestion and limitation as I told, if it were there, I would give Cribl 10 out of 10; since it's not, I'm giving nine out of 10. I am just a user of Cribl; my company has a license with them. I'm not sure if they have a partnership with Cribl or not. I rate Cribl nine out of 10.

Our use cases that we are exploring Cribl for right now are for data parsing and data manipulation.

The feature I appreciate most about Cribl is that it is really easy to use and quick to replicate data models on different data sets. We have over 1,000 log sources, and currently, we have to configure them individually with their own architecture. Cribl allows us to do a copy and paste architecture and saves us a lot of development time. It also makes it easy to add any sort of extra data parsing to specific lines. Ease of use is really our biggest benefit from it.

Something that Cribl could do better is processing time. There is not enough customization to improve performance. An example would be with AWS Lambda functions, the way we were doing it before. There are different strategies where the way we code it could save us more processing time and still have the same price. With Cribl, it is very much set in its ways. If you want better performance, then you have to pay for more resources.

The UI is a very beneficial thing that saves us a ton of time. I mentioned the copy and paste approach and little to no code anymore, as it is all UI interface-based now. There is little to no code that we do other than regex commands. If there was still some aspect of being able to add our own code, we could potentially get better performance. I understand this is the whole use case of Cribl, to remove the technical need aspect. You do not need as many experienced developers; you will pay for software and have to hire an analyst instead of an engineer and save money on wages. For how good the tool is, it would be nice to still have that data engineering aspect.

I have not been using Cribl in my career. We are a company that is interested in investing in it at the moment. However, we do have several teams that have used it and we have also had access to a dev workspace that we have used.

I have not had any issues. So far, everything has been good.

It is pretty scalable, just in terms of cost. If you have any problems, it is probably going to be more about having to pay for more resources.

Currently, we are using Logstash, and we are also exploring a POC with DataBahn. DataBahn is a newer company. They are not as sophisticated as Cribl, and the performance is probably not there, but they make up for it in cost.

Being new to Cribl, the setup was very easy.

For us, it could have been done with one person, but we had different team members involved just for exposure because we were onboarding it with many people. It could have been a one-person implementation, but two to three people would have been a good healthy number.

The current pricing is a little bit above average.

We are using around 25% of what Cribl offers, mainly focusing on log parsing, which is what Cribl started with. We use AWS as our main source of ingestion.

There is little flexibility in pricing. It is simply the market price, and you either pay it or you do not. Cribl has significant capacity to handle high volumes of diverse data types, such as logs and metrics. Cribl can handle almost anything we throw at it, as lonthe g as budget is not an issue.

There is a team in my company that uses them, but they are part of a separate company. We do not have any partnership with them yet.

On a scale of 1-10, I rate Cribl an 8.

Entire logs from my organization go through Cribl and get routed to Splunk and various other destinations. I use it on a large scale in my organization. Cribl Stream is one of my favorite parts. I use Cribl to route the logs to various destinations. It helped us to completely remove the monopoly on Splunk. Not only firewall logs, but also cloud trail logs and many other logs were processed through Cribl.

It helped us to completely remove the monopoly on Splunk, as we previously couldn't have any control over logs and how to optimize them. When we had Cribl in place, it provided a vision and a platform for us to control what we send and how we send it in terms of data passing, data enrichment, and many more things, with massaging the data. It also helped us to open up to many tools where we could send the data to various destinations, as it is vendor-agnostic.

Cribl Stream is good, but I feel they could develop more products apart from Cribl Stream for my use case. I know Search is coming and Data Lake is there, but there can be more innovations in Cribl. They had one good product, which is Cribl Stream, which appears to be the primary revenue source for the company, but there may be many other use cases. They could explore OTel and how to connect with DynaTrace. They are looking specifically for logging, but expanding into metrics and APM would also help.

I have been using Cribl for the past three to four years.

On-premises deployment is something which customers take care of themselves. Earlier versions had quite a few issues, but there are more stable versions now, so it is a good time to start using Cribl.

They are very scalable and good.

They are very good in terms of solving issues. Regarding availability over other time zones, since it is mostly focused on Europe and US, they are starting to build up in New Zealand and other places.

I tried a few other alternatives as POCs, but none of them worked out as effectively as Cribl.

We worked on it for six months. Our infrastructure is complex, so it took almost six months, a couple of quarters.

If you have a good architect and a couple of Cribl staff members to assist, three persons can handle the implementation.

It is feasible and doable. Compared to Splunk, Cribl is cheaper.

Pricing is feasible and doable. Compared to Splunk, Cribl is cheaper.

I tried a few other alternatives as POCs, but none of them worked out as effectively as Cribl.

It has been able to perform to the best of its capabilities. They are able to handle everything with their non-shared architecture. On a scale of 1-10, I would rate Cribl a solid nine.